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All Journal INFOMATEK: Jurnal Informatika, Manajemen dan Teknologi Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi JPPIPA (Jurnal Penelitian Pendidikan IPA) The Indonesian Journal of Computer Science
Christian Dwi Suhendra
Universitas Papua
Humanities Computer Science & IT Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Social Sciences

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DEVELOPMENT OF E-MODULES USING AUGMENTED REALITY IN PHYSICS TEACHING AT HIGH SCHOOL OF MANOKWARI REGENCY Alberto Y T Allo; Christian Dwi Suhendra
JPPIPA (Jurnal Penelitian Pendidikan IPA) Vol. 7 No. 2 (2022): Desember 2022
Publisher : Universitas Negeri Surabaya in collaboration with Perkumpulan Pendidik IPA Indonesia (PPII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jppipa.v7n2.p52-59

Abstract

The development of the physics E-Module at this time really needs to be done because of the very rapid development of information technology and coupled with the Covid-19 pandemic situation which requires the availability of the physics E-Module so that it can assist students in learning physics both face-to-face and virtual learning. Based on preliminary observations made in public high schools and private high schools, it was found that the physics module used was a conventional module, namely the printed version of the physics module and the printed year of the module was out of date, so the module is less relevant when used today. The aim of this research is to develop a high school Physics e-module in Manokwari Regency so that it becomes a valid, effective and practical e-module. The method used is the four-D (4D) method. The population of this study were students of class XI IPA 4 at SMA Negeri 1 Manokwari and class XI IPA at SMA YAPIS Manokwari. This research produces an E-Module of Rotational Dynamics and Rigid Body Equilibrium using Augmented Reality (AR) which can be used interactively by students via mobile devices or computers, where in this E-Module there are simple experiments presented in the form of videos, animations using AR, virtual reality that can be accessed anywhere and anytime so that it can improve the physics learning outcomes of class XI IPA students. The purpose of this research is to produce E-Modules using AR in physics lessons that are practical and effective and can improve student learning outcomes.  
Penerapan K-Means Clustering dalam Menentukan Bidang Magang Mahasiswa Jurusan Teknik Informatika Universitas Papua Sri Putri Aulia Syam; Christian Dwi Suhendra; Lion Ferdinand Marini
INFOMATEK: Jurnal Informatika, Manajemen dan Teknologi Vol. 25 No. 1 (2023): Volume 25 No. 1 Juni 2023
Publisher : Fakultas Teknik, Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/infomatek.v25i1.7585

Abstract

Kampus merdeka merupakan kebijakan Menteri Pendidikan dan Kebudayaan dengan beberapa program yang diterapkan di perguruan tinggi salah satunya adalah magang dan studi independent bersertifikat (MSIB). Program magang memberikan kebebasan kepada mahasiswa untuk memilih bidang magang serta instansi penyedia magang. Namun dalam penerapannya bidang magang yang dipilih belum sesuai dengan kemampuan yang dimiliki mahasiswa. Kajian ini bertujuan untuk menerapkan K-Means Clustering dalam menentukan bidang magang mahasiswa. Studi kasus yang diambil yaitu mahasiswa Jurusan Teknik Informatik Universitas Papua. Kemampuan mahasiswa akan diukur berdasarkan nilai mata kuliah serta menerapkan metode K-Means Clustering untuk mengelompokkan bidang magang mahasiswa. Setelah melakukan pengujian diperoleh nilai DBI terendah yaitu 0.203 dari nilai k=2. Cluster yang terbentuk dalam penelitian ini yaitu cluster_0 dengan 57 data nilai mahasiswa dan cluster_1 dengan 134 data nilai mahasiswa. Dengan metode K-Means Clustering berhasil menentukan bidang magang mahasiswa berdasarkan nilai mata kuliah.
Implementation of Predicting the Availability of Chicken Eggs on Christmas Day Using Artificial Neural Network Backpropagation Arin Nofianti; Christian Dwi Suhendra; Marlinda Sanglise
The Indonesian Journal of Computer Science Vol. 13 No. 2 (2024): Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i2.3800

Abstract

Prediction can be called a science that is used to predict events that are likely to occur in the future based on past events. One of the other prediction methods in circulation is Backpropagation Neural Network. Backpropagation Neural Network (BPNN) is a Neural Network (NN) that is forward in nature and does not have a loop through which signals flow from input neurons to output neurons. This research aims to determine a prediction of egg supply in 2023, especially during Christmas in Manokwari district to meet market and customer needs. By analyzing the availability of egg supplies in the city of Manokwari from January 2018 to December 2022. From the methods used in this research, starting from data collection methods as well as variables and research stages which include the data collection process, data sharing, then training and data testing and validation crosswise, the prediction pattern for the number of egg stocks is 12-16-1, where there are 12 variables in the input layer, then 16 variables in the hidden layer, 1 variable in the output layer, the learning rate value is 0.9 and the value the momentum is 0.1, resulting in a prediction of egg stock in 2023, especially in December, of 131053 eggs. With a MAPE value of 27.4767%. with the results of a feasible prediction model value. With the predicted results, the number of egg stocks in 2023, especially in December (during Christmas celebrations) in Manokwari Regency is 131,053 eggs during December 2023.
Peramalan Persediaan Beras Bulog di Kabupaten Manokwari Menggunakan Autoregressive Integrated Moving Average Eka Indriati; Christian Dwi Suhendra; Lion Ferdinand Marini
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 13, No 2: Agustus 2024
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v13i2.1983

Abstract

Rice is one of the main components in the food sector which plays an important role in maintaining food supply stability. The main challenge in this case is maintaining Bulog's rice supply to remain stable. This research was conducted to support efforts to overcome food supply stability at Perum Bulog Manokwari by forecasting future Bulog rice supplies. The method used to predict Bulog's rice supply is the ARIMA model. From the application of the ARIMA method, the ARIMA(1,0,0) model was obtained with an accuracy level measured by an RMSE value of 107,908.4 and an error percentage of 15.71%. Forecasting Bulog's rice supplies using the ARIMA method is carried out for the next six month period, from January to June 2024.  Keywords: Forecasting; Bulog Rice; ARIMA AbstrakBeras merupakan salah satu komponen utama dalam sektor pangan yang memegang peranan penting dalam menjaga stabilitas pasokan pangan. Tantangan utama dalam hal ini adalah menjaga persediaan beras Bulog agar tetap stabil. Penelitian ini dilakukan untuk mendukung upaya dalam mengatasi stabilitas pasokan pangan di Perum Bulog Manokwari dengan melakukan peramalan terhadap persediaan beras bulog di masa mendatang. Metode yang digunakan dalam melakukan prediksi persediaan beras Bulog adalah Model ARIMA. Dari penerapan metode ARIMA, didapatkan model ARIMA(1,0,0) dengan tingkat akurasi yang diukur dari nilai RMSE sebesar 107.908,4 dan persentase kesalahan sebesar 15,71%. Peramalan persediaan beras Bulog menggunakan metode ARIMA dilakukan untuk periode enam bulan mendatang, mulai dari Januari hingga Juni 2024.   
Co-Authors Alberto Y T Allo Arin Nofianti Eka Indriati Lion Ferdinand Marini Marlinda Sanglise Sri Putri Aulia Syam